code: def setUpClass(cls):
      cls._sess = session.Session()
      with cls._sess:
          cls._a_init_val = np.array([[5.0, 3.0], [-1.0, 0.0]])
          cls._b_init_val = np.array([[2.0], [-1.0]])
          cls._c_val = np.array([[-4.0], [np.nan]])
  
          cls._a_init = constant_op.constant(
              cls._a_init_val, shape=[2, 2], name="a1_init"
          )
          cls._b_init = constant_op.constant(
              cls._b_init_val, shape=[2, 1], name="b_init"
          )
  
          cls._a = variable_v1.VariableV1(cls._a_init, name="a1")
          cls._b = variable_v1.VariableV1(cls._b_init, name="b")
          cls._c = constant_op.constant(
              cls._c_val, shape=[2, 1], name="c"
          )
  
          # Matrix product of a and b.
          cls._p = math_ops.matmul(cls._a, cls._b, name="p1")
  
          # Sum of two vectors.
          cls._s = math_ops.add(cls._p, cls._c, name="s")
  
      cls._graph = cls._sess.graph
  
      # These are all the expected nodes in the graph:
      #   - Two variables (a, b), each with four nodes (Variable, init, Assign,
      #     read).
      #   - One constant (c).
      #   - One add operation and one matmul operation.
      #   - One wildcard node name ("*") that covers nodes created internally
      #     by TensorFlow itself (e.g., Grappler).
      cls._expected_num_nodes = 4 * 2 + 1 + 1 + 1 + 1
  
imports: import numpy
  from tensorflow.core.protobuf import config_pb2
  from tensorflow.python.client import session
  from tensorflow.python.debug.lib import debug_utils
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import test_util
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import resource_variable_ops
  from tensorflow.python.ops import variable_v1
  from tensorflow.python.platform import googletest
label_desc: Use image node_id 1 for calling the DebugUtilsTest obj's underlying member method code with example usage: obj.setUpClass(cls) without return types